Object identification method and related monitoring camera apparatus

ABSTRACT

An object identification method determines whether a first monitoring image and a second monitoring image captured by a monitoring camera apparatus have the same object. The object identification method includes acquiring the first monitoring image at a first point of time to analyze a first object inside a first angle of view of the first monitoring image, acquiring the second monitoring image at a second point of the time different from the first point of time to analyze a second object inside the first angle of view of the second monitoring image, estimating a first similarity between the first object inside the first angle of view of the first monitoring image and the second object inside the first angle of view of the second monitoring image; and determining whether the first object and the second object are the same according to comparison result of the first similarity with a threshold.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to an object identification method and amonitoring camera apparatus, and more particularly, to an objectidentification method of determining whether two monitoring images havethe same object and a related monitoring camera apparatus.

2. Description of the Prior Art

Object identification technology is popularly applied for securitysurveillance; for example, monitoring images captured by the same camerain different periods, or captured by different cameras in the same ordifferent periods, can be applied to execute object comparison andidentification. The monitoring camera is installed on the wall or akickstand, and captures the monitoring image containing a pattern of anobject in a specific angle of view. The conventional objectidentification technology acquires one or some characteristic vectors ofthe object inside the monitoring image, and analyzes similarity of thecharacteristic vectors to determine whether the plural of monitoringimages contains the same object. However, color or pattern of the objectin different capturing orientation may be diverse; for example, thefront side and the rear side of the passerby may show different colorand/or different patterns. The conventional object identificationtechnology easily misjudges a determination result in response todetermination of whether the objects in different monitoring images arethe same. Design of an object identification method capable ofovercoming angle difference of view is an important issue in themonitoring industry.

SUMMARY OF THE INVENTION

The present invention provides an object identification method ofdetermining whether two monitoring images have the same object and arelated monitoring camera apparatus for solving above drawbacks.

According to the claimed invention, an object identification method ofdetermining whether a first monitoring image and a second monitoringimage captured by a monitoring camera apparatus have the same object isdisclosed. The object identification method includes acquiring the firstmonitoring image at a first point of time to analyze a first objectinside a first angle of view of the first monitoring image, acquiringthe second monitoring image at a second point of the time different fromthe first point of time to analyze a second object inside the firstangle of view of the second monitoring image, estimating a firstsimilarity between the first object inside the first angle of view ofthe first monitoring image and the second object inside the first angleof view of the second monitoring image, and determining whether thefirst object and the second object are the same one according to acomparison result of the first similarity with a threshold.

According to the claimed invention, a monitoring camera apparatusincludes an image receiver and an operation processor. The imagereceiver is adapted to capture a first monitoring image and a secondmonitoring image. The operation processor is electrically connected tothe image receiver. The operation processor acquires the firstmonitoring image at a first point of time to analyze a first objectinside a first angle of view of the first monitoring image, acquires thesecond monitoring image at a second point of the time different from thefirst point of time to analyze a second object inside the first angle ofview of the second monitoring image, estimates a first similaritybetween the first object inside the first angle of view of the firstmonitoring image and the second object inside the first angle of view ofthe second monitoring image, and determines whether the first object andthe second object are the same one according to a comparison result ofthe first similarity with a threshold, so as to determining whether thefirst monitoring image and the second monitoring image have the sameobject.

According to the claimed invention, a monitoring camera apparatusincludes a first image receiver, a second image receiver and anoperation processor. The first image receiver is adapted to capture afirst monitoring image. The second image receiver is adapted to capturea second monitoring image. The operation processor is electricallyconnected to the first image receiver and the second image receiver. Theoperation processor acquires the first monitoring image at a first pointof time to analyze a first object inside a first angle of view of thefirst monitoring image, acquires the second monitoring image at a secondpoint of the time different from the first point of time to analyze asecond object inside the first angle of view of the second monitoringimage, estimates a first similarity between the first object inside thefirst angle of view of the first monitoring image and the second objectinside the first angle of view of the second monitoring image, anddetermines whether the first object and the second object are the sameone according to a comparison result of the first similarity with athreshold, so as to determining whether the first monitoring image andthe second monitoring image have the same object.

The object identification method of the present invention can acquirethe characteristic values or vectors about the object located inside thesame angle of view of the first monitoring image and the secondmonitoring image when the object moves in different directions. Thecharacteristic values or vectors acquired by the monitoring images,which contain the object located inside the same or approximate angle ofview, can be compared for improving identification misjudgment resultedfrom angle difference of view. Besides, the object identification methodcan utilize some information of the object, such as the dimension and/orthe visible area ratio, to estimate the related similarity via weightingadjustment, so as to provide the preferred object identificationaccuracy.

These and other objectives of the present invention will no doubt becomeobvious to those of ordinary skill in the art after reading thefollowing detailed description of the preferred embodiment that isillustrated in the various figures and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block diagram of a monitoring camera apparatusaccording to a first embodiment of the present invention.

FIG. 2 is a diagram of positions of an object passing a monitoring rangeof the monitoring camera apparatus along a first direction in differentpoints of time according to the first embodiment of the presentinvention.

FIG. 3 to FIG. 7 are diagrams of images captured by the monitoringcamera apparatus at each point of time shown in FIG. 2.

FIG. 8 is a diagram of positions of the object passing the monitoringrange of the monitoring camera apparatus along a second direction indifferent points of time according to the first embodiment of thepresent invention.

FIG. 9 to FIG. 13 are diagrams of images captured by the monitoringcamera apparatus at each point of time shown in FIG. 8.

FIG. 14 is a flow chart of an object identification method according toan embodiment of the present invention.

FIG. 15 and FIG. 16 are diagrams of images acquired by the monitoringcamera apparatus in one possible specific condition according to thefirst embodiment of the present invention.

FIG. 17 is a functional block diagram of the monitoring camera apparatusaccording to a second embodiment of the present invention.

FIG. 18 and FIG. 19 are diagrams of positions of the object passing themonitoring range of the monitoring camera apparatus in different pointsof time according to the second embodiment of the present invention.

DETAILED DESCRIPTION

Please refer to FIG. 1 to FIG. 14. FIG. 1 is a functional block diagramof a monitoring camera apparatus 10 according to a first embodiment ofthe present invention. FIG. 2 is a diagram of positions of an object Opassing a monitoring range R of the monitoring camera apparatus 10 alonga first direction D1 in different points of time according to the firstembodiment of the present invention. FIG. 3 to FIG. 7 are diagrams ofimages captured by the monitoring camera apparatus 10 at each point oftime shown in FIG. 2. FIG. 8 is a diagram of positions of the object Opassing the monitoring range R of the monitoring camera apparatus 10along a second direction D2 in different points of time according to thefirst embodiment of the present invention. FIG. 9 to FIG. 13 arediagrams of images captured by the monitoring camera apparatus 10 ateach point of time shown in FIG. 8. FIG. 14 is a flow chart of an objectidentification method according to an embodiment of the presentinvention.

The monitoring camera apparatus 10 can include an image receiver 12 andan operation processor 14 electrically connected to each other, and usedto identify the object O moved into the monitoring range R. In theembodiment, the object can represent a passerby, or a moving vehicle orany moving matter. The image receiver 12 can capture a plurality ofimages at several points of time, or receive the plurality of imagescaptured by an external camera at several points of time. The operationprocessor 14 can execute the object identification method of the presentinvention, to determine whether the plurality of images have the sameobject. In addition, the monitoring range R of the monitoring cameraapparatus 10 can be indoor place shown in FIG. 2 to FIG. 7, such as ahallway between outdoor place and inner space of the market; however, anapplication of the monitoring range R is not limited to theabove-mentioned embodiment, for example, the monitoring range R can bethe outdoor place, or connection space containing the indoor space andthe outdoor space.

The monitoring range R of the monitoring camera apparatus 10 (or theimage receiver 12) can have a central axis Ax, and further can bedivided into a first angle of view A1, a second angle of view A2, athird angle of view A3, a fourth angle of view A4 and a fifth angle ofview A5 optionally. The first angle of view A1 and the fifth angle ofview A5 can be set symmetrically, and the second angle of view A2 andthe fourth angle of view A4 can be set symmetrically, which depends ondesign demand. When the object O passes through the monitoring range Rin the first direction D1, the monitoring camera apparatus 10 cansequentially acquire the first monitoring images I1_1, I1_2, I1_3, I1_4and I1_5, which contains the first object O1 respectively located insidethe five angles of view A1˜A5. When the object O passes through themonitoring range R in the second direction D2, the monitoring cameraapparatus 10 can sequentially acquire the second monitoring images I2_1,I2_2, I2_3, I2_4 and I2_5, which contains the second object O2respectively located inside the five angles of view A1˜A5. In thepresent invention, amounts of the angle of view and the monitoring imageare not limited to the above-mentioned embodiment, and depend on thedesign demand.

The object identification method of the present invention can executesteps S100 and S102, to analyze the first monitoring image I1_1 acquiredat the first point of time for searching the first object O1 locatedinside the first angle of view A1, and further to analyze the secondmonitoring image I2_1 acquired at the second point of the time differentfrom the first point of time for searching the second object O2 locatedinside the first angle of view A1. In the meantime, the first angle ofview A1 of the first monitoring image I1_1 and the first angle of viewA1 of the second monitoring image I2_1 can be symmetrically located attwo opposite sides of the central axis Ax. Then, step S104 can beexecuted to estimate a first similarity between the first object O1inside the first angle of view A1 of the first monitoring image I1 andthe second object O2 inside the first angle of view A1 of the secondmonitoring image I2 via specific algorithm. Then, step S106 can beexecuted to compare the first similarity with a predefined threshold. Ifthe first similarity is smaller than or equal to the threshold, thefirst object O1 is different from the second object O2, and step S108can be executed to determine the first object O1 and the second objectO2 are not the same object; if the first similarity is greater than thethreshold, step S110 can be executed to determine the first object O1and the second object O2 are the same.

In step S104, similarity estimation can be executed via a variety ofsimilarity metric function, cosine similarity computation or Euclideandistance computation, which has an aim of extracting characteristicvalues or vectors of the first object O1 and the second object O2 forcomparison; an actual application of the similarity estimation is notlimited to the above-mentioned embodiment. The present inventionpreferably may utilize neural network to extract the characteristicvectors from the first object O1 and the second object O2 for thesimilarity estimation, and then an estimating value of the similarityestimation can be used to identify the object. Further, the presentinvention may utilize the neural network to directly identify the firstobject O1 and the second object O2.

For increasing identification accuracy, the object identification methodcan optionally execute steps S112 and S114 after step S104, to analyzeanother first monitoring image I1_2 acquired at the third point of timefor searching the first object O1 inside the second angle of view A2,and further to analyze another second monitoring image I2_2 acquired atthe fourth point of the time different from the third point of time forsearching the second object O2 inside the second angle of view A2. Then,steps S116 and S118 can be executed to estimate a second similaritybetween the first object O1 inside the first monitoring image I1_2 andthe second object O2 inside the second monitoring image I2_2, andcompute a computed value about the first similarity and the secondsimilarity for comparing with the predefined threshold. If the computedvalue is smaller than or equal to the threshold, step S120 can beexecuted to determine the first object O1 and the second object O2 arenot the same object; if the computed value is greater than thethreshold, step S122 can be executed to determine the first object O1and the second object O2 are the same.

For further increasing the identification accuracy, the objectidentification method can further estimate a third similarity betweenthe first object O1 inside the third angle of view A3 of the firstmonitoring image I1_3 and the second object O2 inside the third angle ofview A3 of the second monitoring image I2_3, a fourth similarity betweenthe first object O1 inside the fourth angle of view A4 of the firstmonitoring image I1_4 and the second object O2 inside the fourth angleof view A4 of the second monitoring image I2_4, and/or a fifthsimilarity between the first object O1 inside the fifth angle of view A5of the first monitoring image I1_5 and the second object O2 inside thefifth angle of view A5 of the second monitoring image I2_5. The computedvalue about the first similarity, the second similarity, the thirdsimilarity, the fourth similarity and the fifth similarity can becompared with the predefined threshold, for determining whether thefirst object O1 and the second object O2 are the same object. Thecomputed value can be a mean value of all the similarity, or the meanvalue of some similarity excluding one or several extreme values.Besides, each image set (which includes one first monitoring image andone second monitoring image having the same angle of view) can beweighted by a related weighting value in accordance with resolution ofthe said image set for computing the computed value; for example, thehigh resolution image can be matched with the high weighting value, andthe low resolution image can be matched with the low weighting value orabandoned, and the computed value can be the mean value of the weightedsimilarity.

The object O may show identical vision details inside the same orapproximate angle of view of the monitoring images. For example, themonitoring images showing the object O inside the same angle of view mayboth capture a front side or a back side of the object O, or a similarratio of a head to a body of the object O, so as to accurately determinethe object in some monitoring images are the same one or not. Thus, whenthe object O enters and leaves the monitoring range R, the monitoringcamera apparatus 10 can acquire at least two monitoring images, whichcontain the object O located at the same angle of view, and thendetermine whether the first object O1 moved in the first direction D1and the second object O2 moved in the second direction D2 are the same.As the same object is confirmed, the object identification method of thepresent invention may count an amount of the object, and can be appliedto customer statistic of the market by recording the amount of guestlounging around the market (such as the object moved into and away fromthe monitoring range); a staying period of the guest in the market canbe acquired via time difference between the foresaid two monitoringimages.

It should be mentioned that the object identification method maydetermine the first object O1 inside the first monitoring image I1_1acquired at the first point of time being the same as the second objectO2 inside the second monitoring image I2_1 acquired at the second pointof the time, and then determine the first object O1 inside the firstmonitoring image I1_1 being the same as the second object inside anothersecond monitoring image (not shown in the figures) acquired at anotherpoint of time different from the first point of time and the secondpoint of the time; in the meantime, a cluster of objects passing throughthe monitoring range R along the second direction D2 may contain twoobjects with similar clothes or appearance, and the objectidentification method can estimate two similarities. One similarityhaving a great value can be used to decide the first monitoring imageI1_1 is matched with the second monitoring image I2_1 acquired at thesecond point of the time, or matched with the another second monitoringimage acquired at the another point of the time. Based on theabove-mentioned function, the monitoring camera apparatus 10 of thepresent invention can include a memory (not shown in the figures)electrically connected to the operation processor 14 for storing someimage information in a short term or a long term.

The object identification method of the present invention not only candetermine similarities of some image sets of the first monitoring imageand the second monitoring image having the object O located at differentangles of view, but also can increase the identification accuracy byother ways. For instance, after step S116, the object identificationmethod can compute a first dimension relevant to the first object O1inside the first angle of view A1 of the first monitoring image I1_1 andthe second object O2 inside the first angle of view A1 of the secondmonitoring image I2_1, and a second dimension relevant to the firstobject O1 inside the second angle of view A2 of the first monitoringimage I1_2 and the second object O2 inside the second angle of view A2of the second monitoring image I2_2. The first object O1 and the secondobject O2 in the first angle of view A1 can have the same or approximatedimension, so that the first dimension can be one dimension about thefirst object O1 or the second object O2, or be a mean value ofdimensions about the first object O1 and the second object O2.Computation of the second dimension can correspond to computation of thefirst dimension, and a detailed description is omitted herein forsimplicity.

The object identification method can utilize the first dimension and thesecond dimension to respectively weight the first similarity and thesecond similarity, and execute step S118 to compare the computed valuecomputed by the weighted first similarity and the weighted secondsimilarity with the predefined threshold, for determining whether thefirst object O1 and the second object O2 are the same one. As shown inFIG. 2 to FIG. 13, the first object O1 and the second object O2 insidethe first angle of view A1 have large dimensions (which are larger thanthe small object inside the second angle of view A2) and can providemore characteristic values or vectors for similarity comparison, so thatthe first similarity can be matched with the greater weighting value(such as the first dimension), and the second similarity has inferioraccuracy and can be matched with the lower weighting value (such as thesecond dimension).

In some specific conditions, a plurality of objects appearing inside thesame angle of view of the monitoring range R may be overlapped to eachother. Please refer to FIG. 15 and FIG. 16. FIG. 15 and FIG. 16 arediagrams of images acquired by the monitoring camera apparatus 10 in onepossible specific condition according to the first embodiment of thepresent invention. An extra object O3 may hide a part of the firstobject O1, and therefore the object identification method can compute afirst visible area ratio relevant to the first object O1 inside thefirst angle of view A1 of the first monitoring image I1_1′ and thesecond object O2 inside the first angle of view A1 of the secondmonitoring image I2_1, and a second visible area ratio relevant to thefirst object O1 inside the second angle of view A2 of the firstmonitoring image I1_2′ and the second object O2 inside the second angleof view A2 of the second monitoring image I2_12.

In one embodiment, a hiding dimension of the first object O1 hid by theextra object O3 can be acquired, and a hiding ratio of the hidingdimension to a whole dimension of the first object O1 can be acquired,and then the first visible area ratio can be computed by subtracting thehiding ratio from a visible dimension of the first object O1 inside thefirst angle of view A1 of the first monitoring image I1_1′; the visiblearea ratio of other objects in the monitoring image can be computedaccordingly, and therefore the embodiment can search one or severalobjects with more characteristic information inside the monitoringimages for identification. In other possible embodiment, the presentinvention can acquire a bounding box of each object, and then utilize asize of the bounding box of the said object hidden by the bounding boxof the extra object to compute the visible area ratio. However,computation of the visible area ratio is not limited to theabove-mentioned embodiments, and any method of computing the visiblearea ratio about one object hidden by another object in the monitoringimage belongs to an actual application of the present invention.

As the embodiment shown in FIG. 15 and FIG. 16, the first visible arearatio inside the first angle of view A1 of the first monitoring imageI1_1′ can be greater than the second visible area ratio inside thesecond angle of view A2 of the first monitoring image I1_2′, so that thefirst similarity and the second similarity in step S118 can be weightedrespectively by the high weighting value and the low weighting value,and then the computed value computed by the weighted first similarityand the weighted second similarity can be compared with the predefinedthreshold, for determining whether the first object O1 and the secondobject O2 are the same one. It should be mentioned that the objectidentification method of the present invention can optionally decidewhether the first visible area ratio and/or the second visible arearatio is over a ratio threshold for a start. If the first visible arearatio and/or the second visible area ratio does not exceed the ratiothreshold, the object in the said angle of view is hidden by the extraobject O3 in a large scale manner and provides the unsatisfactorycharacteristic values or vectors, so that this set of the firstmonitoring image and the second monitoring image can be ignored. If thefirst visible area ratio and/or the second visible area ratio exceed theratio threshold, the first visible area ratio and the second visiblearea ratio can be weighting values for adjustment of the firstsimilarity and the second similarity.

Please refer to FIG. 17 to FIG. 19. FIG. 17 is a functional blockdiagram of the monitoring camera apparatus 10′ according to a secondembodiment of the present invention. FIG. 18 and FIG. 19 are diagrams ofpositions of the object O passing the monitoring range R of themonitoring camera apparatus 10′ in different points of time according tothe second embodiment of the present invention. The monitoring cameraapparatus 10′ can include a first image receiver 16, a second imagereceiver 18 and an operation processor 20 electrically connected witheach other. The first image receiver 16 and the second image receiver 18can respectively capture the first monitoring image and the secondmonitoring image, or can respectively receive the first monitoring imageand the second monitoring image captured by the external camera. In thesecond embodiment, setting of the angles of view where the object islocated inside the monitoring image can be similar to the firstembodiment, and a detailed description is omitted herein for simplicity.The first image receiver 16 and the second image receiver 18 can berespectively disposed on two connected or adjacent hallways, which meansthe object O can leave the monitoring range R of the first imagereceiver 16 and then immediately enter the monitoring range R of thesecond image receiver 18. The second embodiment can divide themonitoring range R into five angles of view A1˜A5 via the central axisAx, as the first embodiment shown in FIG. 2.

The operation processor 20 can execute the object identification methodas mentioned above. First, the object identification method can analyzethe first object O1 inside the first angle of view A1 of the first imagereceiver 16, and the second object O2 inside the first angle of view A1of the second image receiver 18; in the meantime, the first angle ofview A1 of the first monitoring image acquired by the first imagereceiver 16 and the first angle of view A1 of the second monitoringimage acquired by the second image receiver 18 can be located on thesame side of the central axis Ax. Then, the object identification methodcan estimate similarity of the objects O1 and O2, and determine whetherthe first object O1 and the second object O2 are the same according to acomparison of the similarity with the predefined threshold. As the saidfirst embodiment, the second embodiment can synthetically determinesimilarities of the objects inside the angles of view A1˜A5 to increasethe identification accuracy, or can further analyze the dimension and/orthe visible area ratio of the object inside each angle of view A1˜A5, soas to increase the identification accuracy by weighting thesimilarities.

In conclusion, the monitoring camera apparatus can capture themonitoring images about the object located inside all the angles of viewwhen the object enters and leaves the monitoring range. For effectivelyincreasing the object identification accuracy, the object identificationmethod of the present invention can acquire the characteristic values orvectors about the object located inside the same angle of view of thefirst monitoring image and the second monitoring image when the objectmoves in different directions. The characteristic values or vectorsacquired by the monitoring images, which contain the object locatedinside the same or approximate angle of view, can be compared forimproving identification misjudgment resulted from angle difference ofview. Besides, the object identification method can utilize someinformation of the object, such as the dimension and/or the visible arearatio, to estimate the related similarity via weighting adjustment, soas to provide the preferred object identification accuracy.

Those skilled in the art will readily observe that numerousmodifications and alterations of the device and method may be made whileretaining the teachings of the invention. Accordingly, the abovedisclosure should be construed as limited only by the metes and boundsof the appended claims.

What is claimed is:
 1. An object identification method of determiningwhether a first monitoring image and a second monitoring image capturedby a monitoring camera apparatus have the same object, the objectidentification method comprising: acquiring the first monitoring imageat a first point of time to analyze a first object inside a first angleof view of the first monitoring image, wherein a plurality of angles ofview is defined within the first monitoring image along a firstdirection, and the first angle of view of the first monitoring image isa beginning of the plurality of angles of view within the firstmonitoring image; acquiring the second monitoring image at a secondpoint of the time different from the first point of time to analyze asecond object inside the first angle of view of the second monitoringimage, wherein other plurality of angles of view is defined within thesecond monitoring image along a second direction different from thefirst direction, and the first angle of view of the second monitoringimage is a beginning of the plurality of angles of view within thesecond monitoring image; estimating a first similarity between the firstobject inside the first angle of view of the first monitoring image andthe second object inside the first angle of view of the secondmonitoring image; and determining whether the first object and thesecond object are the same one according to a comparison result of thefirst similarity with a threshold.
 2. The object identification methodof claim 1, wherein the monitoring camera apparatus comprises an imagereceiver, a monitoring range of the image receiver has a central axis,and the first angle of view in the first monitoring image and the firstangle of view in the second monitoring image are symmetrically locatedon two opposite sides of the central axis.
 3. The object identificationmethod of claim 1, wherein the monitoring camera apparatus comprises twoimage receivers, a monitoring range of each of the two image receivershas a central axis, and the first angle of view in the first monitoringimage and the first angle of view in the second monitoring image arelocated on the same side of the central axis.
 4. The objectidentification method of claim 1, wherein the monitoring cameraapparatus further captures another first monitoring image at a thirdpoint of time, and another second monitoring image at a fourth point ofthe time different from the third point of time, the objectidentification method comprises: analyzing the first object inside asecond angle of view of the another first monitoring image; analyzingthe second object inside the second angle of view of the another secondmonitoring image; estimating a second similarity between the firstobject inside the second angle of view of the another first monitoringimage and the second object inside the second angle of view of theanother second monitoring image; and determining whether the firstobject and the second object are the same one according to a comparisonresult of a computed value computed by the first similarity and thesecond similarity with the threshold.
 5. The object identificationmethod of claim 4, further comprising: computing a first dimensionrelevant to the first object inside the first angle of view of the firstmonitoring image and the second object inside the first angle of view ofthe second monitoring image; computing a second dimension relevant tothe first object inside the second angle of view of the another firstmonitoring image and the second object inside the second angle of viewof the another second monitoring image; utilizing the first dimensionand the second dimension to respectively weight the first similarity andthe second similarity; and determining whether the first object and thesecond object are the same one according to a comparison result ofanother computed value computed by the weighted first similarity and theweighted second similarity with the threshold.
 6. The objectidentification method of claim 4, further comprising: computing a firstvisible area ratio relevant to the first object inside the first angleof view of the first monitoring image and the second object inside thefirst angle of view of the second monitoring image; computing a secondvisible area ratio relevant to the first object inside the second angleof view of the another first monitoring image and the second objectinside the second angle of view of the another second monitoring image;utilizing the first visible area ratio and the second visible area ratioto respectively weight the first similarity and the second similarity;and determining whether the first object and the second object are thesame one according to a comparison result of another computed valuecomputed by the weighted first similarity and the weighted secondsimilarity with the threshold.
 7. The object identification method ofclaim 6, further comprising: determining whether the first visible arearatio and/or the second visible area ratio is over a ratio threshold;and deciding a weighting value of the first visible area ratio and/orthe second visible area ratio according to a determination result. 8.The object identification method of claim 1, wherein the monitoringcamera apparatus further captures another second monitoring image atanother point of the time different from the first point and the secondpoint of time, the object identification method analyses whether thefirst monitoring image and the another second monitoring image have thesame object, and decides the first monitoring image corresponds to thesecond monitoring image or the another second monitoring image accordingto an analysis result.
 9. A monitoring camera apparatus, comprising: animage receiver capturing a first monitoring image and a secondmonitoring image; and an operation processor electrically connected tothe image receiver, the operation processor acquiring the firstmonitoring image at a first point of time to analyze a first objectinside a first angle of view of the first monitoring image, acquiringthe second monitoring image at a second point of the time different fromthe first point of time to analyze a second object inside the firstangle of view of the second monitoring image, estimating a firstsimilarity between the first object inside the first angle of view ofthe first monitoring image and the second object inside the first angleof view of the second monitoring image, and determining whether thefirst object and the second object are the same one according to acomparison result of the first similarity with a threshold, so as todetermining whether the first monitoring image and the second monitoringimage have the same object; wherein a plurality of angles of view isdefined within the first monitoring image along a first direction, andthe first angle of view of the first monitoring image is a beginning ofthe plurality of angles of view within the first monitoring image;wherein other plurality of angles of view is defined within the secondmonitoring image along a second direction different from the firstdirection, and the first angle of view of the second monitoring image isa beginning of the plurality of angles of view within the secondmonitoring image.
 10. The monitoring camera apparatus of claim 9,wherein a monitoring range of the image receiver has a central axis, andthe first angle of view in the first monitoring image and the firstangle of view in the second monitoring image are symmetrically locatedon two opposite sides of the central axis.
 11. The monitoring cameraapparatus of claim 9, wherein the image receiver further capturesanother first monitoring image at a third point of time, and anothersecond monitoring image at a fourth point of the time different from thethird point of time, the operation processor further analyzes the firstobject inside a second angle of view of the another first monitoringimage, analyzes the second object inside the second angle of view of theanother second monitoring image, estimates a second similarity betweenthe first object inside the second angle of view of the another firstmonitoring image and the second object inside the second angle of viewof the another second monitoring image, and determines whether the firstobject and the second object are the same one according to a comparisonresult of a computed value computed by the first similarity and thesecond similarity with the threshold.
 12. The monitoring cameraapparatus of claim 11, wherein the operation processor further computesa first dimension relevant to the first object inside the first angle ofview of the first monitoring image and the second object inside thefirst angle of view of the second monitoring image, computes a seconddimension relevant to the first object inside the second angle of viewof the another first monitoring image and the second object inside thesecond angle of view of the another second monitoring image, utilizesthe first dimension and the second dimension to respectively weight thefirst similarity and the second similarity, and determines whether thefirst object and the second object are the same one according to acomparison result of another computed value computed by the weightedfirst similarity and the weighted second similarity with the threshold.13. The monitoring camera apparatus of claim 11, wherein the operationprocessor further computes a first visible area ratio relevant to thefirst object inside the first angle of view of the first monitoringimage and the second object inside the first angle of view of the secondmonitoring image, computes a second visible area ratio relevant to thefirst object inside the second angle of view of the another firstmonitoring image and the second object inside the second angle of viewof the another second monitoring image, utilizes the first visible arearatio and the second visible area ratio to respectively weight the firstsimilarity and the second similarity, and determines whether the firstobject and the second object are the same one according to a comparisonresult of another computed value computed by the weighted firstsimilarity and the weighted second similarity with the threshold. 14.The monitoring camera apparatus of claim 9, wherein the monitoringcamera apparatus further captures another second monitoring image atanother point of the time different from the first point and the secondpoint of time, the object identification method analyses whether thefirst monitoring image and the another second monitoring image have thesame object, and decides the first monitoring image corresponds to thesecond monitoring image or the another second monitoring image accordingto an analysis result.
 15. A monitoring camera apparatus, comprising: afirst image receiver capturing a first monitoring image; a second imagereceiver capturing a second monitoring image; and an operation processorelectrically connected to the first image receiver and the second imagereceiver, the operation processor acquiring the first monitoring imageat a first point of time to analyze a first object inside a first angleof view of the first monitoring image, acquiring the second monitoringimage at a second point of the time different from the first point oftime to analyze a second object inside the first angle of view of thesecond monitoring image, estimating a first similarity between the firstobject inside the first angle of view of the first monitoring image andthe second object inside the first angle of view of the secondmonitoring image, and determining whether the first object and thesecond object are the same one according to a comparison result of thefirst similarity with a threshold, so as to determining whether thefirst monitoring image and the second monitoring image have the sameobject; wherein a plurality of angles of view is defined within thefirst monitoring image along a first direction, and the first angle ofview of the first monitoring image is a beginning of the plurality ofangles of view within the first monitoring image; wherein otherplurality of angles of view is defined within the second monitoringimage along a second direction different from the first direction, andthe first angle of view of the second monitoring image is a beginning ofthe plurality of angles of view within the second monitoring image. 16.The monitoring camera apparatus of claim 15, wherein a monitoring rangeof each of the first image receiver and the second image receiver has acentral axis, and the first angle of view in the first monitoring imageand the first angle of view in the second monitoring image are locatedon the same side of the central axis.
 17. The monitoring cameraapparatus of claim 15, wherein the image receiver further capturesanother first monitoring image at a third point of time, and anothersecond monitoring image at a fourth point of the time different from thethird point of time, the operation processor further analyzes the firstobject inside a second angle of view of the another first monitoringimage, analyzes the second object inside the second angle of view of theanother second monitoring image, estimates a second similarity betweenthe first object inside the second angle of view of the another firstmonitoring image and the second object inside the second angle of viewof the another second monitoring image, and determines whether the firstobject and the second object are the same one according to a comparisonresult of a computed value computed by the first similarity and thesecond similarity with the threshold.
 18. The monitoring cameraapparatus of claim 17, wherein the operation processor further computesa first dimension relevant to the first object inside the first angle ofview of the first monitoring image and the second object inside thefirst angle of view of the second monitoring image, computes a seconddimension relevant to the first object inside the second angle of viewof the another first monitoring image and the second object inside thesecond angle of view of the another second monitoring image, utilizesthe first dimension and the second dimension to respectively weight thefirst similarity and the second similarity, and determines whether thefirst object and the second object are the same one according to acomparison result of another computed value computed by the weightedfirst similarity and the weighted second similarity with the threshold.19. The monitoring camera apparatus of claim 17, wherein the operationprocessor further computes a first visible area ratio relevant to thefirst object inside the first angle of view of the first monitoringimage and the second object inside the first angle of view of the secondmonitoring image, computes a second visible area ratio relevant to thefirst object inside the second angle of view of the another firstmonitoring image and the second object inside the second angle of viewof the another second monitoring image, utilizes the first visible arearatio and the second visible area ratio to respectively weight the firstsimilarity and the second similarity, and determines whether the firstobject and the second object are the same one according to a comparisonresult of another computed value computed by the weighted firstsimilarity and the weighted second similarity with the threshold. 20.The monitoring camera apparatus of claim 15, wherein the monitoringcamera apparatus further captures another second monitoring image atanother point of the time different from the first point and the secondpoint of time, the object identification method analyses whether thefirst monitoring image and the another second monitoring image have thesame object, and decides the first monitoring image corresponds to thesecond monitoring image or the another second monitoring image accordingto an analysis result.